基于 OCT/OCTA 的 AI 筛查系统在抗 VEGF 治疗糖尿病性黄斑水肿患者效果评价中的应用

朱明琼 ,  李征 ,  刘茹 ,  田涛 ,  彭婧利 ,  吕倩怡 ,  谭华霞

山东大学耳鼻喉眼学报 ›› 2026, Vol. 40 ›› Issue (01) : 68 -73.

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山东大学耳鼻喉眼学报 ›› 2026, Vol. 40 ›› Issue (01) : 68 -73. DOI: 10.6040/j.issn.1673-3770.0.2024.488
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基于 OCT/OCTA 的 AI 筛查系统在抗 VEGF 治疗糖尿病性黄斑水肿患者效果评价中的应用

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The application of AI screening system based on OCT/OCTA in the evaluation of the effect of anti VEGF treatment in patients with diabetes macular edem

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摘要

目的 分析基于光学相干断层扫描 (optical coherence tomography, OCT) / 光学相干断层扫描血管成像技术 (optical coherence tomography angiography, OCTA) 的人工智能 (artificial intelligence, AI) 筛查系统在抗血管内皮生长因子 (vascular endothelial growth factor, VEGF) 治疗糖尿病性黄斑水肿患者效果评价中的应用效果。方法 选取我院眼科 2022 年 1 月 1 日至 2024 年 1 月 31 日诊治的 120 例糖尿病性黄斑水肿患者,依据糖尿病性黄斑水肿分型分为弥漫水肿型 42 例、囊样水肿型 40 例、混合型黄斑水肿 38 例。所有患者实施抗 VEGF 治疗,疗程均为 3 个月。基于 OCT/OCTA 的 AI 筛查系统对所有患者治疗前后的黄斑中心凹无血管区面积、黄斑中心视网膜厚度、视网膜神经节细胞层厚度、视网膜神经纤维层厚度、视网膜血流密度 (视网膜深层毛细血管丛、视网膜浅层毛细血管丛) 进行测定和比较。结果 所有患者治疗后的黄斑中心凹无血管区面积、黄斑中心视网膜厚度、视网膜神经节细胞层厚度、视网膜神经纤维层厚度、视网膜血流密度均优于治疗前 (P 均 <0.05)。弥漫水肿型、囊样水肿型患者治疗后的黄斑中心凹无血管区面积、黄斑中心视网膜厚度、视网膜神经节细胞层厚度、视网膜神经纤维层厚度、视网膜血流密度优于混合型黄斑水肿患者 (P 均 <0.05)。结论 基于 OCT/OCTA 的 AI 筛查系统可以更为精准的评估不同分型的糖尿病性黄斑水肿患者抗 VEGF 治疗效果,为指导今后临床治疗工作提供助力,值得推广应用。

Abstract

Objective To analyze the application effect of an artificial intelligence (AI) screening system based on optical coherence tomography (OCT) / optical coherence tomography angiography (OCTA) in the evaluation of the efficacy of anti-vascular endothelial growth factor (VEGF) in the treatment of patients with diabetic macular edema. Methods 120 patients with diabetic macular edema diagnosed and treated from January 1, 2022 to January 31, 2024 were selected. According to the diabetic macular edema, they were divided into 42 cases of diffuse edema, 40 cases of cystic edema, and 38 cases of mixed macular edema. All patients underwent anti-VEGF treatment for 3 months. The AI screening system based on OCT/OCTA was used to measure and compare the area of the fovea avascular area, the thickness of the macular central retinal center, the thickness of the retinal ganglion cell layer, the thickness of the retinal nerve fiber layer, and the blood flow density of the retinal blood flow (deep capillary plexus in the retinal layer, and the superficial capillary plexus in the retinal layer) before and after treatment. Results The area of the fovea avascular area, the thickness of the macular central retinal, the thickness of the retinal ganglion cell layer, the thickness of the retinal nerve fiber layer, and the blood flow density of the retinal patients after treatment were better than before treatment (P all <0.05). The area of the fovea avascular area, the thickness of the macular central retinal, the thickness of the retinal ganglion cell layer, the thickness of the retinal nerve fiber layer, and the blood flow density of the retinal blood flow density of the retinal patients after treatment were better than those of the mixed macular edema (P all <0.05). Conclusion The AI screening system based on OCT/OCTA can more accurately evaluate the anti-VEGF treatment effect of patients with different types of diabetic macular edema, providing assistance in guiding future clinical treatment work and is worthy of promotion and application.

关键词

糖尿病性黄斑水肿 / 光学相干断层扫描 / 光学相干断层扫描血管成像技术 / 人工智能 / 抗血管内皮生长因子 / 分型 / 治疗效果

Key words

Diabetic macular edema / Optical coherence tomography / Optical coherence tomography angiography / Artificial intelligence / Anti-vascular endothelial growth factor / Classification / Treatment effect

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朱明琼,李征,刘茹,田涛,彭婧利,吕倩怡,谭华霞. 基于 OCT/OCTA 的 AI 筛查系统在抗 VEGF 治疗糖尿病性黄斑水肿患者效果评价中的应用[J]. 山东大学耳鼻喉眼学报, 2026, 40(01): 68-73 DOI:10.6040/j.issn.1673-3770.0.2024.488

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基金资助

湘南学院科研项目(2022JX165)

湖南省自然区域联合基金项目(2024JJ7034)

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